جست‌وجوی استاد و پژوهشگر

Augustine Ikpehaiمشاهده پروفایل

مدرس ارشد

• Smart Grid
• IoT and Intelligent Infrastructure
• Electric Vehicle (EV) Charging Networks
• +۵ مورد دیگر

Dr. Augustine Ikpehai is a Senior Lecturer in the Department of Engineering and Mathematics at Sheffield Hallam University, part of the College of Business, Technology and Engineering. He joined the university in 2019 after completing post-doctoral research at Manchester Metropolitan University. His expertise spans Smart Grids, IoT, and Intelligent Infrastructure, with a focus on EV charging networks, cyber security, and renewable energy integration. Education: PhD in Smart Grid Communication (Manchester Metropolitan University) MSc in Communication Engineering (Lancaster University) Research Interests: His work addresses EV charging infrastructure, smart wireless power transfer, transactive energy systems, and IoT security in critical infrastructure. He has led projects such as the Innovate UK-funded City Verve IoT initiative and contributed to the EU H2020 Triangulum Smart Cities project. Grants & Projects: Overhead Line Warning System (£581,721 – 2023–2025) Optimal Scheduling of EV-Integrated Multi-Energy Systems (£83,986 – 2022) EU H2020 Triangulum Project (€23M – 2014–2019) Awards: MMU Research Knowledge Exchange Award (2016) UK-China Newton Fund Travel Grant (2019) UK-Brazil Newton Fund Travel Grant (2019) Advising & Labs: Supervises multiple PhD students and collaborates with the Centre for Automation and Robotic Research and Hallam Energy. He has advised projects ranging from hybrid encryption frameworks to hydrogen supply chain dynamics.

Olamide Jogunolaمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Blockchain Technology
• Peer-to-Peer Energy Trading
• +۲ مورد دیگر

Dr. Olamide Jogunola is a Senior Lecturer in Cyber Security in the Department of Computing and Mathematics at Manchester Metropolitan University. She holds a B.Eng. in Electrical Engineering from University of Ilorin, M.Sc. in Networking and Data Communication from Kingston University, and Ph.D. in Electrical Engineering from Manchester Metropolitan University. Her research focuses on cybersecurity for distributed critical infrastructures like smart grids. Research Focus: Investigates blockchain and AI applications for privacy and uncertainty modeling in distributed systems. Current projects examine secure smart contracts, federated learning for intrusion detection, and cyber resilience in IoT-enabled infrastructures. Grant Leadership: Principal Investigator for multiple projects including the £228K 'AI-enabled smart EV charging infrastructure' (Innovate UK/KTP) and £5K EPSRC/SuperGen Network project. Secured over £500K in research funding across 8 projects including EU Horizon 2020 and DFID initiatives. Teaching: Leads undergraduate and postgraduate units in Networks, Computer Networks and Security, and HPC & Big Data. Supervises PhD research on blockchain applications, AI security, and peer-to-peer energy trading.

Yuriy V. Pershinمشاهده پروفایل

استاد

• Condensed Matter Physics
• Emerging Memory Devices
• Unconventional Computing
• +۳ مورد دیگر

Yuriy V. Pershin is a Professor in the Department of Physics and Astronomy at the McCausland College of Arts and Sciences, University of South Carolina. His research focuses on emerging memory devices (e.g., memristors, memcapacitors), unconventional computing paradigms, and 2D materials like graphene. He leads experimental and theoretical investigations into device fabrication, nonlinear dynamics, and nanoscale phenomena. Research Interests: Emerging Memory Devices: Designing memristive systems with memory retention capabilities, modeling their electrical behavior, and exploring their applications in low-power circuits. Unconventional Computing: Developing computing architectures that integrate memory and logic (e.g., neuromorphic networks), demonstrated through FPGA implementations and memristive neural networks. 2D Materials: Studying graphene kinks and antikinks as nanoscale motion carriers, with applications in nanoelectromechanical systems (NEMS). Key contributions include defining rigorous tests for ideal memristors, optimizing Joule-loss reduction in memristive systems, and proposing hardware implementations of memcomputing. His work bridges fundamental physics with applied engineering, leveraging tools like SPICE modeling and molecular dynamics simulations. Publications emphasize theoretical rigor and experimental validation, often addressing controversies in memristor characterization. Notable themes include noise-induced chaos in memcomputing, synchronization in memristive networks, and graphene-based electromechanical systems. Awards and Grants: No specific awards listed, though his work reflects sustained research funding in nanotechnology and device physics. Collaborations span academia and industry, focusing on practical applications of novel materials and circuits. Labs/Teams: His laboratory focuses on interdisciplinary projects at the intersection of physics, electronics, and materials science, with ongoing efforts in device fabrication, circuit emulation, and theoretical modeling.

Joao Pomboمشاهده پروفایل

استاد

• Railway Engineering
• Railway Technology
• Vehicle-Track Interaction
• +۷ مورد دیگر

Joao Pombo serves as Professor of Railway Technology at the Institute of Railway Research, University of Huddersfield, UK. He holds dual appointments in the Department of Engineering within the School of Computing and Engineering. With a PhD and Post-Doc in Mechanical Engineering from the University of Lisbon, Portugal, he brings over 24 years of specialized experience in railway engineering and technology. His academic leadership extends to serving as editor-in-chief of the International Journal of Railway Technology and chairman of the International Conference on Railway Technology series. Professor Pombo's research expertise spans railway vehicle dynamics, pantograph-catenary interaction, structural analysis, and condition monitoring. His work addresses critical challenges in high-speed rail, maintenance engineering, and predictive maintenance systems. He employs advanced methodologies including multibody dynamics, machine learning algorithms, and hardware-in-the-loop testing to solve complex railway engineering problems. His research directly contributes to UN Sustainable Development Goals related to sustainable transport infrastructure and clean energy systems. Analysis of his recent publications reveals a strong focus on advancing railway electrification systems through improved pantograph-catenary interaction models, while increasingly incorporating machine learning techniques for infrastructure optimization and condition monitoring. His work demonstrates consistent innovation in modeling complex railway dynamics, with particular emphasis on real-world applications that enhance safety, efficiency, and sustainability in rail transport systems. Professor Pombo's scientific recognition includes four innovation prizes for his R&D work. He serves on editorial boards for prestigious journals including Multibody System Dynamics and Energies - Electric Vehicles , and has established himself as a leading authority in international railway research circles. Editor-in-chief of International Journal of Railway Technology Chairman of International Conference on Railway Technology series Editorial board member of Multibody System Dynamics Editorial board member of Energies - Electric Vehicles With over 170 publications in refereed journals and international conferences, Professor Pombo actively supervises PhD students and collaborates with leading international research centers and industry partners. His prior three years of industry experience at BOMBARDIER and ALSTOM provides valuable practical context for his academic research. Current projects include developing advanced condition monitoring systems, optimizing railway infrastructure performance, and creating novel analysis tools for railway electrification systems. As a core member of the Institute of Railway Research at the University of Huddersfield, Professor Pombo contributes to one of the world's leading railway research centers. His work with the UKRRIN Centre of Excellence in Rolling Stock demonstrates his commitment to translating academic research into practical industry applications that support railway electrification and infrastructure modernization projects worldwide.

Aman Behalمشاهده پروفایل

استاد

• Rehabilitation Robotics
• Human-Robot Interaction
• Computer Vision
• +۲ مورد دیگر

Dr. Aman Behal is a Professor in the Department of Electrical and Computer Engineering at the University of Central Florida's College of Engineering and Computer Science. He directs the Assistive Robotics and Hybrid Systems laboratories, with research focusing on rehabilitation robotics, human-robot interaction, nonlinear controls, and assistive technologies. His educational background includes a PhD in Electrical Engineering from Clemson University and an M.Tech from Indian Institute of Technology Bombay. Research develops novel interfaces for wheelchair-mounted robotic arms to assist with daily living tasks, supported by NSF funding. Additional projects include computational neuronal network modeling for predictive neurobiology and deep learning approaches for robotic grasping. The UCF-MANUS robotic manipulator system enables real-world evaluation of assistive technologies through clinical collaborations. Recent publications emphasize adaptive control strategies for robotic manipulation, human-robot interaction safety frameworks, and computer vision for autonomous grasping. Work frequently integrates machine learning with control theory for assistive applications. Charles N. Millican Faculty Fellow (2016 onwards) Substantial grant funding includes NSF awards for adaptive human-robot interaction frameworks and social learning in mixed human-robot groups. Current doctoral students investigate neural interfaces, control algorithms, and assistive device applications. Editorial responsibilities include IEEE Transactions on Control Systems Technology and Journal of Aerospace Engineering.

Graziana Cavoneمشاهده پروفایل

استادیار

• Decision Support Systems
• Modeling and Control of Complex Systems
• Transportation Systems Optimization
• +۴ مورد دیگر

Graziana Cavone is an Assistant Professor in Systems and Control Engineering at the University Roma Tre. She holds a Ph.D. in Electronic and Information Engineering from the University of Cagliari and is qualified as an Associate Professor in Automatica. Her research focuses on decision support systems, transportation networks, energy systems, and industrial automation, with expertise in Model Predictive Control (MPC), Petri Nets modeling, and resilient infrastructure design. Education: Ph.D. (Excellent with Honors), Electronic and Computer Engineering, University of Cagliari (2018) Master’s (Summa Cum Laude), Control Engineering, Polytechnic of Bari (2013) Research Interests: Optimization of intermodal transport terminals and railway networks Energy-efficient building management and microgrids Cyber-physical systems in Industry 4.0 Resilient critical infrastructure control Human-robot collaboration and safe ergonomics Grants & Leadership: Principal Investigator for a National Natural Science Foundation of China grant (2020–2021) Recipient of multiple RTD-B and research fellowships in control systems and automation Organizer of international conferences like IEEE CASE 2024 and MED 2021 Labs & Collaborations: Member of the Decision and Control Laboratory at University Roma Tre Collaborations with institutions like Delft University of Technology and Southwest Jiaotong University Industry partnerships with Enel, Fiat Chrysler Automobiles, and Elettric80

Jonathan Nixonمشاهده پروفایل

پژوهشگر

• Wind Energy
• PV-Battery Systems
• Solar Thermal
• +۵ مورد دیگر

Dr. Jonathan Nixon is a Senior Researcher and Associate Director for Research and Engagement at Coventry University's College of Engineering, Environment and Science. With a PhD from Aston University, his work focuses on renewable energy technologies including solar, wind, and bioenergy, particularly in humanitarian contexts such as refugee camps and cold climate environments. He leads the Innovate UK Energy Catalyst Project 'Solar Energy Transitions: Inclusive e-cooking in sub-Saharan Africa' and previously served as co-investigator on the EPSRC-funded Humanitarian Engineering and Energy for Displacement (HEED) project. Education: PhD in Hybrid Solar-Biomass Power Plants from Aston University His research integrates machine learning and Internet of Things (IoT) to optimize renewable energy systems through advanced energy systems modeling , life cycle assessment , and decision support systems . Key expertise areas include: Wind Energy PV-Battery Systems Solar Thermal Thermochemical Conversion Energy Optimization Cold Climate Adaptations Recent publications highlight trends in linear fresnel reflector optimization , biogas seasonal variation , and smart microgrid management across 2022-2024. His work emphasizes energy democratization and SDG7 implementation through community-engaged approaches. Scientific awards include: 2014 Outstanding Reviewer – Emerald Literati Network Awards for Excellence Research collaborations span companies, NGOs, and grassroots organizations with fieldwork in Rwanda, Nepal, and Pakistan. Current PhD projects focus on anaerobic digestion optimization , micro-grid load shedding , and wind turbine operations in cold climates .

• Polymer Electrolytes
• Energy Storage
• Materials Science
• +۲ مورد دیگر

Benjamin Paren is an Assistant Professor in Chemical Engineering and Materials Science at Stevens Institute of Technology. His research develops polymer electrolytes for electrochemical energy applications including batteries and fuel cells, with focus on resource-abundant materials. The Paren Lab investigates ion transport mechanisms using techniques like X-ray scattering and dielectric spectroscopy. Research interests include sodium and magnesium battery systems, anion exchange membranes, and structure-property relationships in energy materials.

Balakumar Balasingamمشاهده پروفایل

دانشیار

• Battery Management Systems
• Human-Machine Interaction
• Signal Processing
• +۳ مورد دیگر

Dr. Balakumar Balasingam is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Windsor, Faculty of Engineering. His research focuses on Battery Management Systems, Human-Machine Systems, Signal Processing, Machine Learning, and Information Fusion. He holds a Ph.D. in Electrical Engineering from McMaster University (2008). He is a Professional Engineer of Ontario and a Senior Member of the IEEE. His work emphasizes robust battery management techniques, including parameter estimation for lithium-ion batteries and real-time state-of-charge/state-of-power estimation. He also investigates human factors in automated systems, leveraging eye-tracking and pupilometry for cognitive load assessment. Key contributions include the book *Robust Battery Management Systems With MATLAB* (Artech House, 2023) and over 100 peer-reviewed articles in IEEE Transactions, Energies, and other journals. Dr. Balasingam directs the Battery Management Systems Lab and Human Machine Systems Lab, advancing innovations in battery diagnostics, autonomous driving interfaces, and adaptive automation. His research integrates signal processing, machine learning, and control systems to address challenges in energy storage and human-technology interaction. His professional affiliations include the International Society of Information Fusion (ISIF) and active roles in IEEE technical committees. Research grants include funding for battery thermal management systems and cognitive load detection in automated driving scenarios.

Hussein Abdeltawabمشاهده پروفایل

استادیار

• Power system modernization
• Smart grid technologies
• Energy management
• +۱۰ مورد دیگر

Hussein Abdeltawab is an Assistant Professor specializing in power system modernization and smart grid technologies. His research integrates artificial intelligence with energy systems to improve grid operation and planning. Education Ph.D. in Electrical Engineering (2017), University of Alberta MSc in Electrical Engineering with distinction (2012), Cairo University BSc in Electrical Engineering with distinction (2012), Cairo University Research Focus His work addresses: Smart grid technologies and renewable energy integration Energy storage optimization and distributed resources Deep learning applications for multi-carrier systems Transportation-energy infrastructure synergy (e.g., smart highways) He leads the Intelligent Power and Energy Management Lab, focusing on AI-driven energy solutions. Publications Trends His research spans 2012–2024, with recent works emphasizing: Neural architecture search for hybrid energy systems Wildfire resilience in distribution grids Piezoelectric energy harvesting for smart infrastructure Deep reinforcement learning for EV battery stations Hydrogen-infrastructure integration frameworks

Joseph Dvorakمشاهده پروفایل

دانشیار

• Agricultural Machinery
• Autonomous Vehicles
• Hybrid Powertrains
• +۳ مورد دیگر

Joseph Dvorak is an Associate Professor in the Department of Biosystems and Agricultural Engineering at the University of Kentucky's Martin-Gatton College of Agriculture, Food and Environment. His research focuses on enabling human producers to manage large agricultural areas efficiently using advanced machinery systems. Key areas include sensors, autonomous vehicles, hybrid powertrains, and vehicle routing optimization. Research interests concentrate on machinery processes for precision agriculture, particularly investigating variability's effect on power usage and developing solutions through hybrid drivetrains and autonomous control systems. This work aims to increase production while minimizing inputs, contributing to the Water-Energy-Food Nexus. Education includes a Ph.D. from Kansas State University (2012), M.S. and B.S. from Oklahoma State University. Articles demonstrate consistent focus on agricultural technology innovations, particularly in autonomous systems (77% of recent publications), energy efficiency (23%), and remote sensing applications (33%).

Simon Fooمشاهده پروفایل

استاد

• Photovoltaics
• Multi-junction III-V compound Solar Cells
• Organic/Polymer Solar Cells
• +۵ مورد دیگر

Simon Foo is a tenured Professor of Electrical and Computer Engineering at the FAMU-FSU College of Engineering, part of Florida A&M University and Florida State University. He has held roles including Department Chair (2010–2018) and has been a professor since 2005. His research focuses on photovoltaics and machine learning, with over 150 publications and 50+ graduated students. He leads 20+ funded projects from agencies like NASA, DOE, NSF, and industries like Boeing and Airbus. Education: Ph.D. (1988), M.S. (1985), and B.S. (1983) in Electrical Engineering from the University of South Carolina. Research Interests: Photovoltaics (multi-junction solar cells, quantum dots, perovskites) and machine learning applications in energy systems, control, and healthcare. His lab develops AI-driven solutions for renewable energy optimization and battery management systems. Key Awards: Teaching Incentive Award (1995) Teacher of the Year (2001 & 2010) Engineering Research Awards (2004 & 2008) Two Best Paper Awards (2001 & 2004) Advising & Grants: Mentored over 50 graduate students in photovoltaics and AI. Secured grants from NASA, DOE, NSA, NSF, and industry partners. Current projects include battery state-of-charge estimation and AI for aircraft fire detection systems. Labs & Collaborations: Collaborates with Airbus on aircraft safety systems and maintains an active research group focused on renewable energy and AI integration. His lab is currently full and not accepting students until 2027.

Alexandra M. Newmanمشاهده پروفایل

استاد

• Applied Optimization
• Transportation Logistics
• Mine Production Scheduling
• +۵ مورد دیگر

Alexandra M. Newman is a Professor in Mechanical Engineering at Colorado School of Mines and serves as the Director of the Operations Research with Engineering Program. Her research focuses on applied optimization across diverse domains including mining, energy systems, healthcare, and sports scheduling. Education: BS in Applied Mathematics, University of Chicago MS in Operations Research, University of California, Berkeley PhD in Industrial Engineering and Operations Research, University of California, Berkeley Her work addresses complex logistical challenges in underground mine planning, renewable energy deployment, and counterinsurgency modeling. Recent publications emphasize microgrid resilience, electric vehicle energy consumption, and optimization of hybrid solar power systems. Notable research trends include: Integration of sustainability metrics in mining and energy systems Advancements in dispatch optimization for renewable energy Application of stochastic modeling to athletic and healthcare scheduling

Mahshid Amirabadiمشاهده پروفایل

دانشیار

• Power Electronics
• Renewable Energy Systems
• Microgrids
• +۴ مورد دیگر

Mahshid Amirabadi is an Associate Professor in the Department of Electrical and Computer Engineering at Northeastern University. Her research focuses on power electronics for renewable energy systems, microgrids, variable speed drives, and wireless power transfer. She holds a PhD from Texas A&M University and has held academic positions at the University of Illinois at Chicago and Northeastern University since 2013. Education PhD, Electrical Engineering (Power-Power Electronics), Texas A&M University (2013) MS, Electrical Engineering (Power-Power Electronics), University of Tehran (2006) BS, Electrical Engineering (Electronics), Shahid Beheshti University (2002) Research Interests Dr. Amirabadi’s work centers on designing efficient and reliable power converters, particularly for renewable energy integration and high-frequency applications. She develops universal converters to streamline energy conversion processes across various systems. Key Awards NSF CAREER Award (2021) IEEE Transactions on Power Electronics Best Paper Awards (2020, 2021) Best Paper at IEEE ECCE (2016) Grants & Advising She leads NSF-funded research on universal SiC-based converters and has secured grants from the Office of Naval Research and ARPA-E. Her advisees include PhD students Ehsan Afshari and M. Khodabandeh, contributing to impactful publications in top journals. Labs & Teams Her lab focuses on advanced converter topologies and their applications in renewable energy systems, collaborating on projects like ARPA-E’s universal power converter initiatives.

Rodrigo Morales Alvaradoمشاهده پروفایل

مدرس

• Internet of Things
• Android and Mobile Devices
• Refactoring
• +۱ مورد دیگر

Rodrigo Morales Alvarado is a full-time Lecturer at the Department of Computer Science & Software Engineering within the Gina Cody School of Engineering and Computer Science at Concordia University. His research focuses on applying Search-Based Software Engineering to improve software design quality, particularly in emergent systems like mobile devices and Internet of Things (IoT). He holds a BSc (2005) and MSc (2008) from the Polytechnic of Mexico, and a PhD (2017) from Polytechnique Montréal. His doctoral work on automated software refactoring earned the Best Thesis Award 2017. His professional experience includes roles as a software developer in the banking sector and a postdoctoral fellowship at Ptidej Lab under Prof. Yann-Gaël Guéhéneuc. He organizes the IEEE/ACM International Workshop on Software Engineering Research and Practices for IoT (SERP4IoT), co-chaired since 2019. His publications span journals like IEEE TSE and conferences such as ICSE and SANER, addressing topics like energy-efficient mobile apps and IoT software challenges. He teaches undergraduate and graduate courses in software engineering, including SOEN 341, SOEN 6481, and SOEN 6611. Awards include the CONACYT Merit Scholarship for Mexican students abroad. He actively reviews for journals like the IEEE Internet of Things and conferences like SANER, and contributed to initiatives like the Concordia Shuffle fundraiser. His tools include EARMO (energy-aware refactoring) and MoMIT (JavaScript interpreter miniaturization for IoT).